First, all the neighboring forest polygons next to the currently occupied one were
scored using the weighted parameters. For example, say that a neighboring
polygon had the following values: food quality = 4, cover quality = 1, slope =
5, proximity to water bodies = 1, and proximity to roadside salt pools = 3. Then
its score would have been equal to the following:

Next the scores were turned into preferences by determining
the two habitat quality ranks on either side of the score and applying a linear
interpolation to obtain a precise preference value. For example, the score
3.10 obtained above fell between the habitat quality rankings of 3 and 4, which had
values of 0.125 and 0.25 respectively. Consequently, the score 3.10 became 0.125 + (3.10
-3) * (0.25 -0.125) =
0.1375.

These preferences were normalized to 100%. The normalized
preferences were laid out along a line from 0 to 1, a random number was selected
between 0 and 1, and the preference that bound the selected random number was
determined and its corresponding polygon chosen. If, however, this chosen
polygon was the one previously visited or the one before that, the process was repeated until a new polygon was selected. This was to avoid the moose returning too soon to a previously visited forest polygon. If the
current polygon had only one or two neighbors, the first neighbor was
selected in both cases. If the polygon had no neighbors, the moose returned
to the forest polygon it had visited before the previous one. It was anticipated that
at that point the moose would pick a different neighboring forest polygon and not end up
in the same dead end.

It was clear that individual moose had distinct home ranges from the moose movement GPS data. Each moose’s starting location was assumed to be the center of its circular home range, the radius of which was entered into the moose location shape field. All moose
ranges were given a radius of 10 km, a value somewhat larger than the 6 km of
Voigt et al. (2000) but which approximated the real study-area moose. This
radius was used when the moose was traveling to check if it exceeded its
home range limit. If this happened, then the moose had to choose a different
polygon to move to. This rule was relaxed to just a warning in the final version
of the model, because otherwise the moose tended to get stuck on the perimeter of its home range.